We need your help. We are making a large financial investment to accelerate our pivot from an analytics-as-a-service company to a product company. We are rapidly expanding our client base. Our core product offering is a both a machine learning platform and a member and provider engagement software that will grow into a recommendation system.
To make this all happen, we are looking for scientists, economists, and engineers to mature the product and help us execute our 3-year product road map. If you’ve got what it takes and are interested in the position description below, we can’t wait to share our product backlog with you!
What you’ll do
As a data engineer, you will be responsible for the entire client data pipeline. This includes intake of client data, transforming this data to our standards, manipulating the data for machine learning, and transforming the data for our OPUS application. Along the way, you will also be enhancing existing pipeline as well as create new ones to ensure our team can scale and support new clients. If this interests you, read on.
- Design and develop data integration (ETL) processes (including ingestion, cleansing, unification, etc.)
- Automate the processing of customer data feeds
- Design and develop tools to support data profiling and data quality methodologies
- Work with our data science team to assist with data prep and data enrichment for predictive modelling
- Engage with application development team to ensure all data points are included per application specification
- Provide periodic support to the customer success team
Skills & Experience
- BS / MS in Computer Science, Engineering or applicable experience
- 3+ years of experience with ETL principles
- 3+ years of SQL experience; Microsoft SQL Server or PostgreSQL preferred
- Excellent verbal and written communication
- Knowledge of data manipulation methodologies
- Ability to discover and highlight unique patterns/trends within data and solve complex problems
- Keen understanding of database design principles; has worked within staging, data warehouse, and analytic database environments
- Comfortable working with very large data sets and VLDB environments
- Experience with version control tools: Git preferred
- Understanding of data science and predictive modelling concepts preferred
- Experience working within host vendor and cloud-based infrastructure; AWS and Rackspace preferred
- Familiarity with statistical software R and BI tool Tableau a plus
- Familiarity with healthcare data a plus
A little more about Decision Point
We are a rapidly growing healthcare company in the healthcare market. This year, we’ll nearly double in size. Our products & support services advise healthcare insurance and provider organizations on how to best target and engage their members so that members make better health decisions. The result? Our clients can identify their sickest members before they get sick and connect these members with the health and social support services they need to manage their condition.
Our innovative approach to member and provider engagement strategy and orchestration leverages cutting edge machine learning techniques to better inform clients on how to take action. Guided by our team of industry recognized healthcare and technology experts, with backgrounds from NASA, Microsoft, E&Y, health plans, and other great organizations, we are putting healthcare data to good use.